matplotlib 基本操作
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2022-07-14 10:05:25
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使用matplotlib时遇到一些问题，特记录在此
1. 图表中中文不能正常显示
新建pyhton脚本文件 matplotlib_sup_ch.py
# matplotlib_sup_ch.py
import matplotlib.pyplot as plt
plt.rcParams['font.sans-serif'] = ['SimHei']
plt.rcParams['axes.unicode_minus'] = False
cplt = plt
在需要绘图的地方将cplt导入使用，就可以解决中文不能正常显示的问题
# test.py
from matplotlib_sup_ch import cplt as plt
import math
import numpy as np
if __name__ == '__main__':
x = list(np.linspace(0, 2*math.pi, 100)) # 从[0, 2π]中取100个数据点
y = [math.cos(e) for e in x]
plt.title('cos曲线')
plt.xlabel('弧度')
plt.plot(x, y)
plt.show()
2. matplotlib中可用的颜色列表
新建color.py
# color.py
cnames = {
'aliceblue': '#F0F8FF',
'antiquewhite': '#FAEBD7',
'aqua': '#00FFFF',
'aquamarine': '#7FFFD4',
'azure': '#F0FFFF',
'beige': '#F5F5DC',
'bisque': '#FFE4C4',
'black': '#000000',
'blanchedalmond': '#FFEBCD',
'blue': '#0000FF',
'blueviolet': '#8A2BE2',
'brown': '#A52A2A',
'burlywood': '#DEB887',
'cadetblue': '#5F9EA0',
'chartreuse': '#7FFF00',
'chocolate': '#D2691E',
'coral': '#FF7F50',
'cornflowerblue': '#6495ED',
'cornsilk': '#FFF8DC',
'crimson': '#DC143C',
'cyan': '#00FFFF',
'darkblue': '#00008B',
'darkcyan': '#008B8B',
'darkgoldenrod': '#B8860B',
'darkgray': '#A9A9A9',
'darkgreen': '#006400',
'darkkhaki': '#BDB76B',
'darkmagenta': '#8B008B',
'darkolivegreen': '#556B2F',
'darkorange': '#FF8C00',
'darkorchid': '#9932CC',
'darkred': '#8B0000',
'darksalmon': '#E9967A',
'darkseagreen': '#8FBC8F',
'darkslateblue': '#483D8B',
'darkslategray': '#2F4F4F',
'darkturquoise': '#00CED1',
'darkviolet': '#9400D3',
'deeppink': '#FF1493',
'deepskyblue': '#00BFFF',
'dimgray': '#696969',
'dodgerblue': '#1E90FF',
'firebrick': '#B22222',
'floralwhite': '#FFFAF0',
'forestgreen': '#228B22',
'fuchsia': '#FF00FF',
'gainsboro': '#DCDCDC',
'ghostwhite': '#F8F8FF',
'gold': '#FFD700',
'goldenrod': '#DAA520',
'gray': '#808080',
'green': '#008000',
'greenyellow': '#ADFF2F',
'honeydew': '#F0FFF0',
'hotpink': '#FF69B4',
'indianred': '#CD5C5C',
'indigo': '#4B0082',
'ivory': '#FFFFF0',
'khaki': '#F0E68C',
'lavender': '#E6E6FA',
'lavenderblush': '#FFF0F5',
'lawngreen': '#7CFC00',
'lemonchiffon': '#FFFACD',
'lightblue': '#ADD8E6',
'lightcoral': '#F08080',
'lightcyan': '#E0FFFF',
'lightgoldenrodyellow': '#FAFAD2',
'lightgreen': '#90EE90',
'lightgray': '#D3D3D3',
'lightpink': '#FFB6C1',
'lightsalmon': '#FFA07A',
'lightseagreen': '#20B2AA',
'lightskyblue': '#87CEFA',
'lightslategray': '#778899',
'lightsteelblue': '#B0C4DE',
'lightyellow': '#FFFFE0',
'lime': '#00FF00',
'limegreen': '#32CD32',
'linen': '#FAF0E6',
'magenta': '#FF00FF',
'maroon': '#800000',
'mediumaquamarine': '#66CDAA',
'mediumblue': '#0000CD',
'mediumorchid': '#BA55D3',
'mediumpurple': '#9370DB',
'mediumseagreen': '#3CB371',
'mediumslateblue': '#7B68EE',
'mediumspringgreen': '#00FA9A',
'mediumturquoise': '#48D1CC',
'mediumvioletred': '#C71585',
'midnightblue': '#191970',
'mintcream': '#F5FFFA',
'mistyrose': '#FFE4E1',
'moccasin': '#FFE4B5',
'navajowhite': '#FFDEAD',
'navy': '#000080',
'oldlace': '#FDF5E6',
'olive': '#808000',
'olivedrab': '#6B8E23',
'orange': '#FFA500',
'orangered': '#FF4500',
'orchid': '#DA70D6',
'palegoldenrod': '#EEE8AA',
'palegreen': '#98FB98',
'paleturquoise': '#AFEEEE',
'palevioletred': '#DB7093',
'papayawhip': '#FFEFD5',
'peachpuff': '#FFDAB9',
'peru': '#CD853F',
'pink': '#FFC0CB',
'plum': '#DDA0DD',
'powderblue': '#B0E0E6',
'purple': '#800080',
'red': '#FF0000',
'rosybrown': '#BC8F8F',
'royalblue': '#4169E1',
'saddlebrown': '#8B4513',
'salmon': '#FA8072',
'sandybrown': '#FAA460',
'seagreen': '#2E8B57',
'seashell': '#FFF5EE',
'sienna': '#A0522D',
'silver': '#C0C0C0',
'skyblue': '#87CEEB',
'slateblue': '#6A5ACD',
'slategray': '#708090',
'snow': '#FFFAFA',
'springgreen': '#00FF7F',
'steelblue': '#4682B4',
'tan': '#D2B48C',
'teal': '#008080',
'thistle': '#D8BFD8',
'tomato': '#FF6347',
'turquoise': '#40E0D0',
'violet': '#EE82EE',
'wheat': '#F5DEB3',
'white': '#FFFFFF',
'whitesmoke': '#F5F5F5',
'yellow': '#FFFF00',
'yellowgreen': '#9ACD32'
}
绘图时颜色不够丰富，从color.py导入cnames直接使用
# test.py
from matplotlib_sup_ch import cplt as plt
import math
import numpy as np
from color import cnames
if __name__ == '__main__':
x = list(np.linspace(0, 2*math.pi, 100)) # 从[0, 2π]中取100个数据点
y = [math.cos(e) for e in x]
color_values = list(cnames.values())
plt.title('cos曲线')
plt.xlabel('弧度')
for i in range(0, len(color_values)):
y = [math.cos(i*e) for e in x]
plt.plot(x, y)
plt.show()
3.设置坐标轴刻度间隔及范围
# test.py
from matplotlib_sup_ch import cplt as plt
from matplotlib.pyplot import MultipleLocator
# 设置坐标轴刻度
ax = plt.gca()
# 设置x轴刻度为5
x_major_locator = MultipleLocator(5)
ax.xaxis.set_major_locator(x_major_locator)
# 设置y轴刻度为0.05
y_major_locator = MultipleLocator(0.05)
ax.yaxis.set_major_locator(y_major_locator)
# 设置坐标轴范围
plt.xlim(-1, 95) # 设置x轴范围为[-1, 95]
plt.ylim(0, 1) # 设置y轴范围为[0, 1]
4. 设置显示图例
from matplotlib_sup_ch import cplt as plt
import math
import numpy as np
if __name__ == '__main__':
x = list(np.linspace(0, 2*math.pi, 100)) # 从[0, 2π]中取100个数据点
y1 = [math.cos(e) for e in x]
y2 = [math.sin(e) for e in x]
plt.plot(x, y1)
plt.plot(x, y2)
plt.legend(['cos', 'sin'], loc='best') # loc参数决定图例的放置位置，更多选择详见 https://blog.csdn.net/lanluyug/article/details/80002273
plt.show()
trick: plt.legend()需要放置在plt.plot()之后图例才可以正确显示
5. 图像保存
path = 'img 将要保存的位置'
plt.savefig(path)
plt.close() # 如果有多张图像保存，可保证图像在绘制时不发生累积现象